Density Functional Theory Calculations of Lithium Adsorption and

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Density Functional Theory Calculations of Lithium Adsorption and Insertion to Defect-Free and Defective Graphene Yasuharu Okamoto J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.6b05458 • Publication Date (Web): 16 Jun 2016 Downloaded from http://pubs.acs.org on June 21, 2016

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Density Functional Theory Calculations of Lithium Adsorption and Insertion to Defect-Free and Defective Graphene Yasuharu Okamoto*

The IoT Devices Research Laboratories, NEC Corporation, 34 Miyukigaoka, Tsukuba, Ibaraki, 305-8501 Japan

E-mail: [email protected]

*To whom correspondence should be addressed.

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ABSTRACT Density-functional theory calculations with periodic boundary conditions were done to clarify the interaction between lithium atoms and a graphene sheet. Three types of graphene sheets—defect-free, containing carbon vacancies VCn (n = 1, 2, 3, 4, 6, 10, 13, 16, and 24), and their hydrogen terminated ones—were examined in this study. We found that a lithium atom inserted into bare carbon vacancy VCn (n ≥ 3) is more stable than that in bulk lithium metal and it is trapped by the vacancy. On the other hand, a lithium atom inserted into the hydrogen terminated carbon vacancies is less stable than that in bulk metal. These results suggest that the electrochemical in-plane insertion of lithium ions into the bare carbon vacancies is possible whereas the insertion into the hydrogen terminated vacancies is unlikely because the precipitation of lithium metal is energetically more favorable.

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INTRODUCTION There are several studies reporting that graphene-based carbon materials can accommodate much larger number of lithium atoms than the conventional graphite-based ones as the anode of lithium ion batteries (LIBs).1-5 The high-capacity of the material makes it promising as a next generation LIB that is required for environmentally friendly battery electric vehicles (EVs) and plug-in hybrid EVs. Yoo et al. reported that graphene nano sheet (GNS) can store lithium atoms as much as 540 mAh/g and this value can be extended to 730 mAh/g and 784 mAh/g by the incorporation of macromolecules of CNT and C60 to the GNS, respectively.1 Moreover, Wu et al. showed that the reversible capacity of N-doped (B-doped) graphene reaches 872 mAh/g (1227 mAh/g).3 It is noteworthy that these capacities are much higher than the theoretical capacity of graphite (372 mAh/g). It should be noted that Li atoms substantially become Li+ ions by donating electrons to carbon atoms when they are incorporated into graphite. Therefore, the Li atoms in graphite attractively interact with up and down graphene layers whereas the attractive interaction comes only from one sheet in the case of the adsorption on a graphene sheet. This suggests that the strength of lithium binding is weaker on a graphene sheet than that in graphite. Indeed first-principles calculations of Li adsorption on a defect-free graphene sheet showed that the adsorbed Li is less stable than bulk Li metal,6-9 which implies that the process of Li metal precipitation is energetically more favorable than Li adsorption on graphene. Experimental studies, by contrast, showed that Li extraction from graphene continues linearly up to 3 V [vs. Li/Li+].1-5 This indicates that quite a few Li atoms in graphene-based materials are strongly trapped in them. Although it was suggested that graphene edges might be related to its high Li storage capacity,8 simple

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comparison of the number of atoms on edge and in plane of graphene implies that very small nano-sized graphene flakes comprised of a few hundreds of atoms are needed to explain the high capacity experimentally observed. Moreover, edges of anode active material of LIBs are usually covered by solid electrolyte interphase with low electron conductivity, which may affect the reversibility of Li movement in charge and discharge processes. These considerations suggest that it is important to examine defects in a graphene sheet to understand the characteristics of lithium storage in graphene-based anode materials and to provide suggestions for further improvement of Li storage performance. Graphene-based anode materials contain intentionally or non-intentionally introduced defects especially if they are formed through graphite oxides (GOs). Note that the thermal reduction process of GOs inevitably introduces carbon vacancies or carbon hole defects into a graphene sheet because oxygen atoms that are initially introduced as epoxy and hydroxyl groups are removed from the sheet by evolving carbon containing species such as CO and CO2 during the thermal reduction process.10,11 These holes are likely to affect the interaction of lithium with graphene, which in turn influences the capacity of the anode active material. There have been a number of first-principles studies aimed at providing a better understanding of physical and chemical phenomena of Li on graphene.6-9,12-16 These studies include Li adsorption on graphene with mono- and di- vacancies,6,7 effect of grain boundary7 or edge,12 and transportation characteristics of lithium ion5,6,12,14,15 which is important because it is related with power characteristics of LIBs. We consider that it is necessary to deal with defects in a graphene sheet to explain experimentally observed large Li storage capacity. Although Li extraction continues at around 3 V [vs.

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Li/Li+] in the experiments, little is known about what chemical environment of graphene traps Li atoms. In spite of these preceding studies, elucidation of Li interaction with large carbon vacancies still remains to be done. In particular we examined a hole comprised of multi-vacancies in graphene as observed in the experiment.11 Multi-vacancies in a graphene sheet are energetically more favorable than the situation where the equivalent number of C atoms is removed from the sheet as mono-vacancies because the total number of dangling bonds is lower in the former than that in the latter. Although there are complicated O-related defects after thermal reduction of GOs by Hammer’s method as in ref. 11,it seems to be difficult to construct a plausible atomic model for such a large defective structure and this situation may be different when Brodie’s method and hydrogen reduction are used for moderate oxidation and thorough removal of oxygen from graphene. In this paper, we have performed density functional theory (DFT) calculations to examine lithium insertion and adsorption in a graphene sheet with and without carbon vacancies. We first assessed the accuracy of our calculations by comparing the preceding calculations of lithium adsorption on a defect-free graphene sheet. Then, we examined in-plane insertion of lithium into a graphene sheet containing carbon vacancies. We found that bare carbon vacancies strongly bind lithium atom in in-plane insertion way into the graphene sheet except for mono- and di-vacancies. On the other hand, the lithium insertion into the hydrogen terminated carbon vacancies becomes endothermic when we set bulk metal as the energy reference of lithium. This shows that although carbon vacancies significantly enhance the attractive interaction between lithium and graphene, hydrogen termination weakens the interaction to the extent that observed on defect-free graphene.

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COMPUTATIONAL METHODS All first-principles calculations were done by using the Quantum Espresso (ver. 4. 2. 1) program package.17 Calculations of the lattice parameters, ionic positions, and electronic structures were made in accordance with the framework of DFT under the periodic boundary conditions. All ionic positions in the computational cell were fully relaxed in all calculations by using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. The generalized gradient approximation (GGA) to the exchange-correlation functional formulated by Perdew, Burke, and Ernzerhof (PBE9618) were used in the calculation. Although the consideration of van der Waals (vdW) force is essential in graphite in order to evaluate the attractive force between graphene layers, the force is less important in this study because we deal with a single-layer graphene with no interlayer interaction. In addition, electrostatic force is more dominant than vdW force in the interaction between Li and defect-free graphene. Furthermore, in the case of Li and defective graphene (in particular for bare carbon vacancies), the interaction somewhat takes on the character of covalent bonding. These situations can be properly treated by GGA functional employed in this study. Ultrasoft pseudopotentials for C, H, and Li atoms were employed in the calculation. Note that the pseudopotential of Li includes the nonlinear core correction.19 Plane-wave basis sets with cut-off energies of 30 and 300 Ry were respectively used for the expansion of wave functions and charge density. Brillouin zone (BZ) integration was done by using 3×2×1 k-point sampling unless otherwise stated. Figure 1 shows a single-layer graphene sheet which was modeled by a 6×5√3

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rectangle computational cell (14.78 × 21.33 Å) containing 120 carbon sites. The graphene layers are separated by 14.78 Å in the setting of periodic boundary condition along z-axis. The optimized C=C bond length in the cell is 1.422 Å which agrees with measured value of graphite (1.421 Å20). The accuracy of the present computation method was further checked by comparing with preceding studies in the next section. In the following, we summarize the definitions of equilibrium redox potential associated with Li movement into and out of a graphene sheet, and formation energy of carbon vacancy per the number of removed carbon atoms from the graphene sheet. The equilibrium redox potential measured from bulk lithium metal corresponding to lithium injection from m to m+n atoms in the computational cell, or equivalently lithium extraction from m+n to m atoms (hereafter denoted by Vav(m↔m+n)) is defined as,21-23

where E(graphene + Li(n)) and E(Li), respectively, stand for the total energy of the graphene sheet with containing n lithium atoms in the computational cell and the total energy of bulk lithium (per atom). Note that 1/n in the right hand side of the above equation means that the potential is the average value of injection/extraction process of n lithium atoms. Note also that the energy reference of lithium is not an isolated atom in gas phase but the bulk metal in this definition and negative potential means that Li adsorption is energetically unfavorable in comparison with bulk Li metal precipitation. Then the formation energy of carbon vacancy made by removing n carbon atoms from the graphene sheet (hereafter denoted by Ef(VCn)) is defined as

where E(graphene–VCn) and E(C), respectively, stand for the total energy of the

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graphene sheet containing a vacancy VCn and the total energy of graphene per carbon atom.

RESULTS AND DISCUSSION A. Reliability of the Computational Method We first checked the accuracy of the calculated energies in terms of the number of k-points for BZ-integration, the energy cutoffs for wave function and charge density (Ecut[wf, ch]), and the size of computational cell by examining a Li atom adsorption energy (Eads) on a defect-free graphene sheet. Note that Eads is defined as Eads = E(graphene + Li) - {E(Li) + E(graphene)}, where E(x) stands for the total energy of species x and E(Li) corresponds to the energy of bulk Li metal (per atom). Table 1 shows the results of Li adsorption with 4×4 periodicity. We found that the difference of Eads in between two cut-off energy calculations is no more than 1%. This shows that Ecut[wf, ch] = (30 Ry, 300 Ry) calculation provides well converged results with respect to the cut-off energies. We also found that 3×3×1 k-point sampling is comparable to 5×5×1 sampling. We then examined Li adsorption energy on a defect-free graphene sheet by using 6× 5√3 periodic model comprised of 120 carbon atoms (Figure 1). The results are listed in Table 2. It is noteworthy that 3×2×1 and 5×3×1 k-point samplings give similar Eads in terms of both magnitude and sign, while on the other hand the gamma-point (single k-point) sampling predicts too attractive Li-graphene interaction and it leads to a qualitatively wrong result that Li adsorption on graphene is energetically more favorable than bulk Li precipitation. Although the density of state of the defect-free graphene is zero at the Fermi level, we found that the gamma-point sampling generates

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an erroneous state at the level which acts as a kind of dangling bond and binds Li atom strongly. This is why the gamma-point sampling results in a false prediction. Hereafter, we use 3×2×1 k-point sampling for the 6×5√3 periodic model in this study. In comparison with preceding studies,6,8 except for the gamma-point sampling in Table 2, our results in Tables 1 and 2 agree well with the results of 0.315 and 0.190 eV for 6×6 and 9×9 periodic models, respectively.6 It is noteworthy that positive Eads corresponds to the situation where the adsorbed Li is energetically unfavorable in comparison with bulk Li metal from its definition.Our calculations also agree with the result in ref. 6 of -1.096 eV when an isolated atom is used as the energy reference of Li instead of bulk Li metal (value in parenthesis in Tables 1 and 2). On the other hand, the magnitude of them is somewhat smaller than the result of LDA calculation of 1.598 eV (Li atom reference) with the 4×4 periodic model.16

B. Lithium Adsorption/Insertion on/in Graphene Sheets with Carbon Vacancies. As pointed out by several theoretical studies and reconfirmed above subsection, defect-free graphene sheets are not promising as lithium storage material because Li adsorption is energetically less favorable than the bulk Li precipitation which might result in the formation of undesirable dendrite that causes short circuit. We then examined whether or not carbon vacancies affect the adsorption property of graphene. First, the formation energy of carbon vacancy in a graphene sheet, Ef(VCn), was calculated for nine vacancies of n = 1, 2, 3, 4, 6, 10, 13, 16, and 24. Figures 2 and 3, respectively, show the optimized local structure around the vacancy and the formation energy of it. It is noteworthy that the small-size vacancies are less stable than the large-size ones. This is in particular true of mono vacancy that has very high formation

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energy of 8.07 eV. These results suggest that gathering small vacancies to form a larger multi-vacancy is energetically more favorable than the situation where small vacancies are scattered over the graphene sheet because the number of dangling bonds decreases by forming a larger multi-vacancy when the same number of carbon atoms is removed from the graphene sheet. Actually, there are large carbon vacancies in the STEM image of the reduced graphene oxide.11 We then examined the lithium adsorption/insertion energies Eads on/in carbon vacancies VCn and the results are shown in Figure 4. Note that Li insertion here means that a Li atom is placed in-plane of the graphene sheet—in small vacancies the center of VCn is the energetically favorable position. We found that in-plane insertions of Li into mono- and di-vacancies are endothermic. These vacancies are much too small to accommodate the Li with exothermic reaction unlike the large multi-vacancies. Moreover, in the case of VC2 and VC4 vacancies, the exothermicity of lithium adsorption became smaller than VC1 and VC3 vacancies. This is because VC2 and VC4 vacancies are stabilized by substantially forming five member rings through rebonding the dangling bonds (Figure 2). It was found that Li adsorption just above the vacancy is metastable and relaxes to in-plane Li in the graphene sheet during the geometry optimization when the vacancy size n is equal to or larger than 6. This is the reason why the adsorption energies are only shown in cases n = 1, 2, 3, and 4 in Figure 4. It is noteworthy that in-plane insertion energy of Li into VCn is from -3.18 to -2.50 eV when n is equal to or larger than 6. This shows that the equilibrium redox potentials of such insertion are approximately 3 V, which suggests that the trapping of Li in these vacancies might be a candidate for explaining high Li extraction potential observed in the experiments.1-5

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As stated, the center of the vacancy is an energetically favorable site for the in-plane insertion of Li except for VC16 and VC24 where the edge of these vacancies is more attractive for Li because the center of these vacancies is too far to bond with the dangling bonds at the edge. The large energy gain through the Li insertion apparently suggests that Li atoms are easily trapped by the vacancies instead of penetrating them and enhancing the transportation property. However, the situation may change when the concentration of Li around the vacancy increases as shown by a molecular dynamics simulation of collective penetration of Li through a graphene hole (see Supporting Information S1 and S2). As discussed in the previous subsection, defect-free graphene does not much exert attractive force on lithium. This seems to be disadvantageous for increasing Li storage capacity, which in turn directs our attention to introducing a relatively large vacancy to enhance the Li storage capacity of the graphene sheet. In view of this, we focused on how the introduction of VC24 vacancy enhances the Li storage capacity. The rim of VC24 is comprised of the alternating patterns of arm-chair and zigzag edges. We found that Li prefers to bond not to zigzag sites but to arm-chair sites because the adsorption on the latter sites are more stable by 0.34 eV than the former ones. Thus, the six arm-chair sites are expected to be occupied by Li atoms at the first priority. These sites are indeed stable for Li atoms and the equilibrium redox potential of the addition of six Li atoms Vav(0 ↔ 6) is 2.14 V [vs. Li/Li+]. We then examined Li adsorption on the graphene surface near the VC24 and VC24Li6 defects. The dangling bonds of VC24 are terminated by 6 Li atoms in VC24Li6 as shown in Figure 5a. The equilibrium redox potentials of the adsorption were evaluated with respect to the hexagonal hollow sites labelled 1-6 in the figure and the calculated

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potentials are shown in Figure 5b. Note that Vav(6 ↔ 7) corresponds to the Li adsorption on the graphene containing VC24Li6 ,whereas Vav(0 ↔ 1) corresponds to the Li adsorption on the graphene containing VC24 where the dangling bonds of the vacancy being intact. It is notable that Li adsorption on sites near the VC24 and VC24Li6 defects (i.e. sites 3-6) leads to higher potential than that on the sites away from them (i.e. site 1 and 2). Moreover, these potentials are positive unlike the negative potential on defect-free graphene. It is also notable that the calculated potentials of VC24Li6 do not much different from those of VC24. We then additionally put 12 Li atoms on the hollow sites of near VC24Li6. In the initial geometry before relaxation 6 Li atoms were first placed on the one side and the other 6 Li atoms were placed on the opposite side. The equilibrium redox potentials of the Li addition are 0.846 and 0.690 V [vs. Li/Li+] for Vav(6 ↔ 12) and Vav(12 ↔ 18), respectively. However, we found that further addition of a Li atom leads to a negative potential. Thus, the composition of Li18C96 (Li1.125C6) seems to be an upper limit of the lithium storage capacity in the present model, which is slightly higher capacity than that in graphite (LiC6). There are two notes of caution in the present computational models: The one is that large vacancies in the anode active materials might bring about undesirable side effects such as the degradation reaction of solvent molecules with the vacancies. The other is that although the present model deals with an infinite sheet without boundary, actual material is finite and has edges. Thus, somewhat more Li atoms may be trapped at edges as the edges of graphene ribbons bind Na atoms strongly in ref. 21.

C. Lithium Adsorption/Insertion on/in Graphene Sheets with Hydrogen Terminated

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Carbon Vacancies. Finally we examined the influence of the hydrogen termination of the dangling bonds of the vacancies. As expected, hydrogen termination causes significant change in chemical environment of graphene containing carbon vacancies. Figure 5b also shows the case where Li atom is adsorbed on 1-6 sites of the graphene containing VC24H12 in which all the dangling bonds of VC24 are terminated by hydrogen atoms. It is obvious that these sites only weakly interact with the Li atom because their equilibrium redox potentials are negative irrespective of the adsorption sites and the potentials are close to the one on defect-free graphene, which is quite different from Li adsorption on graphene near the bare VC24 defect. In order to clarify the influence of the dangling bonds on the attractive interaction between Li and graphene, we examined the differential charge density of Li adsorption on the site numbering 4 in Figure 5a near the VC24 defect with and without hydrogen termination. The calculated results are shown in Figure 6. The differential charge density (δρ) was defined as δρ = ρ(graphene+Li) - {ρ(graphene) + ρ(Li)} and the silver lobes in the figure correspond to the isosurface of ca. +0.0011 e/Å3. In both panels of the figure, we observe the accumulation of the charge density between Li and carbon atoms beneath of it. However, in the case of Li adsorption on bare carbon vacancy (top panel of the figure), it is clear that the enhancement of the charge density through the dangling bond (designated by a red arrow in the figure) further contributes to increase the attractive interaction between Li and graphene. The energy of in-plane insertion of Li into hydrogen terminated vacancies (VC1H3, VC2H4, VC3H5, VC4H3, VC6H6, VC10H8, VC13H9, VC16H10, and VC24H24) was calculated and the results are shown as triangles in Figure 4. We found that all insertion energies are

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endothermic and the magnitude of endothermicity does not necessarily decrease as the size of the vacancy becomes larger. It is significantly endothermic as much as 1.797 eV even in the largest vacancy of VC24H12. Thus, at least the vacancies examined here, a Li atom does not easily pass through the hydrogen terminated carbon vacancies. Hydrogen terminated carbon vacancies are too repulsive for Li to penetrate the graphene containing them.

CONCLUSIONS DFT calculations were performed to investigate adsorption (insertion) property of lithium on (into) a graphene sheet with and without carbon vacancy. We found that the graphene containing bare carbon vacancy strongly traps lithium atoms by their dangling bonds and the strength of trapping decreases as the number of Li atoms near the vacancy increases. We also found that the hydrogen termination of the carbon vacancies significantly reduces the interaction between lithium and graphene to the extent that observed on lithium adsorption on defect-free graphene.

ACKNOWLEDEMENT The author thanks Prof. Yoshiaki Matsuo, Dr. Noriyuki Tamura and Dr. Qian Cheng for helpful discussion on graphene oxide. This work was partially supported by the Japan Science and Technology Agency (Advanced Low Carbon Technology Research and Development Program).

Supporting Information Available. Supporting figure of snapshot of molecular dynamics simulation of collective penetration of Li through VC24 vacancy and movie

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file of the molecular dynamics simulation. This information is available free of charge via the Internet at http://pubs.acs.org.

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FIGURE CAPTIONS Figure 1: Defect-free graphene sheet modeled by 6×5√3 rectangular cell containing 120 carbon sites. Figure 2: Optimized local structures around vacancy VCn (n = 1, 2, 3, 4, 6, 10, 13, 16, and 24). Figure 3: Formation energy of Ef (VCn) (n = 1, 2, 3, 4, 6, 10, 13, 16, and 24). Figure 4: Energy for in-plane insertion of Li into vacancy VCn (n = 1, 2, 3, 4, 6, 10, 13, 16, and 24; solid diamonds), Lithium adsorption energy on VCn (n=1, 2, 3, and 4; open squares), and energy for in-plane insertion of Li into hydrogen terminated vacancies (VC1H3, VC2H4, VC3H5, VC4H3, VC6H6, VC10H8, VC13H9, VC16H10, and VC24H12; triangles). Figure 5: a) Optimized structure of graphene containing VC24Li6 defect. Numbering 1-6 shows the sites of Li adsorption. b) Relationship between adsorption site and the equilibrium redox potential of the Li adsorption on graphene containing VC24 (Vav(0 ↔ 1); diamonds), on graphene containing VC24Li6 (Vav(6 ↔ 7); squares), and on graphene containing VC24H12 ( Vav(0 ↔ 1); triangles). Figure 6: Differential charge density of Li adsorption on the site numbering 4 in Figure 5a near the VC24 defect. a) VC24 defect without H termination, and b) VC24H12 defect with H-termination. Sky blue, green, and pink balls and sticks stand for, C, H, and Li atoms, respectively. Silver lobes correspond to the isosurface of ca. +0.0011 e/Å3.

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REFERENCES 1. Yoo, E.; Kim, J.; Hosono, E.; Zhou, H.-S.; Kudo, T.; Honma, I. Large Reversible Li Storage of Graphene Nanosheet Families for Use in Rechargeable Lithium Ion Batteries. Nano Lett. 2008, 8, 2277-2282. 2. Wang, G.; Shen, X.; Yao, J.; Park, J. Graphene Nanosheets for Enhanced Lithium Storage in Lithium Ion Batteries. Carbon, 2009, 47, 2049-2053. 3. Wu, Z.-S.; Ren, W.; Xu, L.; Li, F.; Cheng, H.-M. Doped Graphene Sheets As Anode Materials with Super High Rate and Large Capacity for Lithium Ion Batteries. ACS Nano, 2011, 5, 5463-5471. 4. Reddy, A. L. M.; Srivastava, A.; Gowda, S. R.; Gullapalli, H.; Dubey, M.; Ajayan, P. M. Synthesis of Nitrogen-Doped Graphene Films For Lithium Battery Application. ACS Nano, 2010, 4, 6337-6342. 5. Lian, P.; Zhu, X.; Liang, S.; Li, Z.; Yang, W. Wang, H. Large Reversible Capacity of High Quality Graphene Sheets as an Anode Material for Lithium-Ion Batteries. Electrochim. Acta, 2010, 55, 3909-3914. 6. Zhou, L.-J.; Hou, Z. F.; Wu, L.-M. First-Principles Study of Lithium Adsorption and Diffusion on Graphene with Point Defects. J. Phys. Chem. C 2012, 116, 21780-21787. 7. Zhou, L.-J.; Hou, Z. F.; Wu, L.-M.; Zhang, Y.-F. First-Principles Studies of Lithium Adsorption and Diffusion on Graphene with Grain Boundaries. J. Phys. Chem. C. 2014, 118, 28055-28062. 8. Lee, E.; Persson, K. A. Li Absorption and Intercalation in Single Layer Graphene and Few Layer Graphene by First Principles. Nano Lett. 2012, 12, 4624-4628. 9. Liu, M.; Kutana,A.; Liu, Y.; Yakobson, B. I. First-Principles Studies of Li Nucleation on Graphene. J. Phys. Chem. Lett. 2014, 5, 1225-1229. 10. Acik, M.; Lee,G.; Mattevi, C.; Pirkle, A.; Wallace, R. M.; Chhowalla, M.; Cho, K.; Chabal, Y. The Role of Oxygen during Thermal Reduction of Graphene Oxide Studied by Infrared Absorption Spectroscopy. J. Chem. Phys. C, 2011, 115, 19761-19781. 11. C Gómez-Navarro, C.; Meyer, J. C.; Sundaram, R. S.; Chuvilin A.; Kurasch, S.; Burghard, M.; Kern, K.; Kaiser, U. Atomic Structure of Reduce Graphene Oxide. Nano lett. 2010, 10, 1144-1148. 12. Uthaisar, C.; Barone, V. Edge Effects on the Characteristics of Li Diffusion in Graphene. Nano Lett. 2010, 10, 2838-2842. 13. Song, J.; Ouyang, B.; Medhekar, N. V. Energetics and Kinetics of Li Intercalation in Irradiated Graphene Scaffolds. ACS Appl. Mater. Interfaces 2013, 5, 12968-12974.

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14. Fan, X.; Zheng, W.; Kuo, J.-L. Adsorption and Diffusion of Li on Pristine and Defective Graphene ACS Appl. Mater. Interfaces 2012, 4, 2432-2438. 15. Zheng, J.; Ren, Z.; Guo, P.; Fangd, L.; Fana, J. Diffusion of Li+ ion on graphene: A DFT study. Appl. Suf. Sci. 2011, 258, 1651-1655. 16. Khantha, M.; Cordero, N. A.; Molina, L. M.; Alonso, J. A.; Girifalco, L. A. Interaction of Lithium with Graphene: An Ab Initio Study. Phys. Rev. B. 2004, 70, 125422. 17. Giannozzi, P.; Baroni, S.; Bonini, N.; Calandra, M.; Car, R.; Cavazzoni, C.; Ceresoli, D.; Chiarotti, G. L.; Cococcioni, M.; Dabo, I.; et al. QUANTUM ESPRESSO: A Modular and Open-source Software Project for Quantum Simulations of Materials. J. Phys. Condens. Matter, 2009, 21, 395502-19. 18. Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865-3868. 19. Louie, S. G.; Froyen, S.; Cohen, M. L. Nonlinear Ionic Pseudopotentials in Spin-Density-Functional Calculations. Phys. Rev. B, 1982, 26, 1738-1742. 20. David, R. L.; eds., HANDBOOK of CHEMISTRY and PHYSICS 75th edition CRC Press, Inc. 1994. 21. Okamoto, Y. Density Functional Theory Calculations of Alkali Metal (Li, Na, and K) Graphite Intercalation Compounds. J. Phys. Chem. C, 2014, 118, 16–19. 22. Okamoto, Y. Ambivalent Effect of Oxygen Vacancies on Li2MnO3: A First-Principles Study. J. Electrochem. Soc. 2012, 159, A152-A157. 23. Okamoto, Y. Dynamical Aspects of Lithiation of a Nanosized Silicon Cluster. J. Phys. Chem. C, 2011, 115, 25160-25164.

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The Journal of Physical Chemistry

Table 1: The dependence of adsorption energy (Eads) of a lithium atom on a defect free graphene sheet with 4×4 periodic model in terms of cut-off energy of wave function and charge density (Ecut(wf, ch)), and k-point sampling for Brillouin Zone integration. Ecut (wf, ch) [Ry] (30, 300) (35,350) (30,300) (35,350) k-points a

Eads [eV]

3×3×1

3×3×1

5×5×3

5×5×3

0.423 (-1.122)

0.427 (-1.119)

0.411 (-1.134)

0.411 (-1.134)

a

Total energy of bulk lithium metal is taken as the energy reference of lithium and value in parenthesis is the Li adsorption energy with respect to an isolated Li atom in gas.

Table 2: Adsorption energy (Eads) of a lithium atom on a defect free graphene sheet with 6×5√3 periodic model containing 120 carbon atoms. Cut-off energy is set to Ecut (wf, ch) = (30 Ry, 300 Ry). k-points a

Eads [eV]

Gamma

3×2×1

5×3×1

-0.154 (-1.700)

0.387 (-1.158)

0.377 (-1.168)

a

Total energy of bulk lithium metal is taken as the energy reference of lithium and value in parenthesis is the Li adsorption energy with respect to an isolated Li atom in gas.

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Figure 1

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Figure 3

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Figure 4

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Figure 5a

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Figure 5b

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Figure 6

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